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← Optimization & Theory
Machine Learning
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Optimization & Theory
›
Learning Theory
5,312 papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss
COLT 2020
ODE-Inspired Analysis for the Biological Version of Oja’s Rule in Solving Streaming PCA
COLT 2020
PAC learning with stable and private predictions
COLT 2020
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks
COLT 2020
Root-n-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank
COLT 2020
Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices
COLT 2020
Bessel Smoothing and Multi-Distribution Property Estimation
COLT 2020
Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes
COLT 2020
Provably efficient reinforcement learning with linear function approximation
COLT 2020
Approximate is Good Enough: Probabilistic Variants of Dimensional and Margin Complexity
COLT 2020
Universal Approximation with Deep Narrow Networks
COLT 2020
On Suboptimality of Least Squares with Application to Estimation of Convex Bodies
COLT 2020
Exploration by Optimisation in Partial Monitoring
COLT 2020
A Closer Look at Small-loss Bounds for Bandits with Graph Feedback
COLT 2020
Learning Over-Parametrized Two-Layer Neural Networks beyond NTK
COLT 2020
On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels
COLT 2020
Better Algorithms for Estimating Non-Parametric Models in Crowd-Sourcing and Rank Aggregation
COLT 2020
Tight Lower Bounds for Combinatorial Multi-Armed Bandits
COLT 2020
Lipschitz and Comparator-Norm Adaptivity in Online Learning
COLT 2020
Extending Learnability to Auxiliary-Input Cryptographic Primitives and Meta-PAC Learning
COLT 2020
A Nearly Optimal Variant of the Perceptron Algorithm for the Uniform Distribution on the Unit Sphere
COLT 2020
Reasoning About Generalization via Conditional Mutual Information
COLT 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
COLT 2020
Open Problem: Model Selection for Contextual Bandits
COLT 2020
Open Problem: Tight Convergence of SGD in Constant Dimension
COLT 2020
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